Collaborative applications of our method to computationally account for surface site heterogeneity have deepened our knowledge of this effect and increased our experience in its modelling. In particular, we have observed alterations of the surface site affinity distribution with increasing age of the immobilized molecules. In collaboration with the laboratory of Dr. Michael Tarlov at NIST, we have embarked on the development of an assay where antibodies are immobilized on gold surfaces, with the goal to correlate surface heterogeneity imaged by AFM with the functional distribution observed by SPR. An integral component of most biosensors is the optical detection of bound protein, which is usually refractive index based. The common assumption is that all proteins have the same refractive index increment. We set out to test this assumption by developing a bioinformatics tool that can predict the distribution of protein refractive index of all known proteins. Incidentally, we found some lens crystallins to be significant outliers, and have studied related sequences from different species. Our prediction software will allow one to account for abnormal signal increments from proteins with unusual amino acid composition, increasing the accuracy in the quantitation of surface-bound material. This may be significant when assessing binding stoichiometries.